A Trust Case-Based Model Applied to Agents Collaboration

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Author(s): Felipe Boff (Lutheran University of Brazil (ULBRA), Brazil)and Fabiana Lorenzi (Lutheran University of Brazil (ULBRA), Brazil)
Copyright: 2019
Pages: 16
Source title: Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7368-5.ch070

Keywords: Artificial Intelligence / Human-Computer Interaction / Information Science Reference / Social Sciences & Humanities

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Abstract

This chapter shows an approach for developing a method that uses case-based reasoning (CBR) for calculating trust levels in agents' collaboration. The proposed development foresees all interactions between agents are considered in the updating process of general trust level. These collaborations are also stored in a CBR database. Each new interaction calculates a situational trust level based on similar cases. This trust level will be weighed against the global trust level, creating an indicator based on the requested collaboration without excluding the collaboration history.

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A Trust Case-Based Model Applied to Agents Collaboration

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